code: def __init__(self) -> None:
      super().__init__()
      model = ResNet(Bottleneck, [3, 4, 6, 3])  # ResNet50
      modelc1 = nn.Sequential(*list(model.children())[:3])
      modelc2 = nn.Sequential(*list(model.children())[4:8])
      modelc1[0] = nn.Conv2d(
          6,
          64,
          kernel_size=(7, 7),
          stride=(2, 2),
          padding=(3, 3),
          bias=False,
      )
      self.net = nn.Sequential(modelc1, modelc2)
  
imports: from typing import Callable, Dict, List, Optional, Type
  import torch
  from torch import nn
  from kornia.core import Module, Tensor, concatenate, stack
  from kornia.utils.helpers import map_location_to_cpu
label_desc: Use image node_id 1 to create a new EncoderDeFMO object from inherited base classes: Module with example: obj = EncoderDeFMO()